LeTra: a leaf tracking workflow based on convolutional neural networks and intersection over union.

Background: The study of plant photosynthesis is essential for productivity and yield. Thanks to the development of high-throughput phenotyping (HTP) facilities, based on chlorophyll fluorescence imaging, photosynthetic traits can be measured in a reliable, reproducible and efficient manner. In most state-of-the-art HTP platforms, these traits are automatedly analyzed at individual plant level, but information at leaf level is often restricted by the use of manual annotation.

Interpreting the variation in particle size of ground spice by high-resolution visual and spectral imaging: A ginger case study.

High-resolution (HR) visual imaging and spectral imaging are common computer vision-based techniques used for food quality analysis and/or authentication based on the interaction of light and material surface and/or composition. The particle size of ground spices is an important morphological feature that affects the physico-chemical properties of food products containing such particles. This study aimed to interpret the impact of particle size of ground spice on its HR visual profile and spectral imaging profile using ginger powder as a representative spice powder model.

Insect exuviae as soil amendment affect flower reflectance and increase flower production and plant volatile emission.

Soil composition and herbivory are two environmental factors that can affect plant traits including flower traits, thus potentially affecting plant-pollinator interactions. Importantly, soil composition and herbivory may interact in these effects, with consequences for plant fitness. We assessed the main effects of aboveground insect herbivory and soil amendment with exuviae of three different insect species on visual and olfactory traits of Brassica nigra plants, including interactive effects.

High-Resolution Analysis of Growth and Transpiration of Quinoa Under Saline Conditions.

The Plantarray 3.0 phenotyping platform was used to monitor the growth and water use of the quinoa varieties Pasto and selRiobamba under salinity (0-300 mM NaCl). Salinity reduced the cumulative transpiration of both varieties by 60% at 200 mM NaCl and by 75 and 82% at 300 mM NaCl for selRiobamba and Pasto, respectively.

Hyperspectral imaging system based on a single-pixel camera design for detecting differences in tissue properties.

Optical spectroscopy can be used to distinguish between healthy and diseased tissue. In this study, the design and testing of a single-pixel hyperspectral imaging (HSI) system that uses autofluorescence emission from collagen (400 nm) and nicotinamide adenine dinucleotide phosphate (475 nm) along with differences in the optical reflectance spectra to differentiate between healthy and thermally damaged tissue is discussed. The changes in protein autofluorescence and reflectance due to thermal damage are studied in ex vivo porcine tissue models.